Value of household availability profiles for last-mile routing

Abstract

Failed deliveries are a major challenge in last-mile logistics, increasing costs and emissions and reducing service quality. Household availability prediction offers a promising approach by aligning delivery attempts with the likelihood of successful handover. However, its real-world value remains unclear. This paper evaluates the impact of household availability profiles (APs) using empirical data and optimization-based experiments. APs are derived from the German Time Use Survey and combined with real shipment data from a German logistics service provider. Routing instances are solved using the Vehicle Routing Problem with Availability Profiles (VRPAP) under varying levels of availability information (0% 100%). Results show that increasing AP coverage significantly reduces failed deliveries and improves service performance. At the same time, travel distances remain stable, indicating no increase in routing inefficiency. However, routing costs rise due to time-based effects, particularly as waiting times are allowed and not fully captured in the cost modeling approach.